The Limits of Startup Strategy

This study examines how the profit-maximizing strategic decisions of growth-driven startups are constrained by the personal motivations of their utility-maximizing founders. In a novel experimental approach that integrates psychology, economics, and strategy research, we apply priming techniques to study entrepreneurial decision-making. We prime the "entrepreneurial identity" of startup founders and then study how a variation in identity salience influences their willingness to make certain choices in hypothetical scenarios.

2019-07-08

2019-08-31

We measure entrepreneurs' stated willingness to take each of the hypothetical strategic decisions described in the "Interventions" section, and the difference between primed and non-primed entrepreneurs. Each scenario is a 5-point Likert item, with possible responses as "Very Unlikely" (1), "Unlikely" (2), "Neutral" (3), "Likely" (4), "Very Likely" (5). We define an outcome variable "Strategic Commitment Score," as the average of each subject's answers, and study this variable in several ways:

(a) First, we run a simple regression showing whether treatment (a binary variable representing those that are primed) predicts a higher level of Strategic Commitment Score.

(b) We also study the distribution of these effects by using machine learning methods that allow us to recover the shape of the effects based on observables. In particular, we apply the honest tree method of Athey and Wagner (2015) and the sorted effects method of Chernozukhov et al (2018).

(c) Finally, we study how the difference in Strategic Commitment Scoreis determined by differences in the underlying characteristics of subjects. To do so, we run interaction models where we interact our treatment with the pre-treatment characteristics and then estimate flexible functions of pre-treatment characteristics with the estimated effects from (b).

We perform the analysis described in "Primary Outcomes" independently on each hypothetical scenario. We do not have any priors at this moment on how their shape or magnitudes will be different.

We also add the following analyses:
(a) Changing our main outcome variable to a binary measure that is equal to 1 if the subjects choose "Likely" or "Very Likely" and 0 otherwise to study LPM, and logit specifications on the odds (or probability change) of being likely choose.

(b) Only for Study 1, the impact of being more 'entrepreneurial' (as defined through the word choice tests) on the Strategic Commitment Score as well as the impact of treatment across this distribution.

This study examines how the profit-maximizing strategic decisions of growth-driven startups are constrained by the personal motivations of their utility-maximizing founders. In a novel experimental approach that integrates psychology, economics, and strategy research, we apply priming techniques to study entrepreneurial decision-making. We prime the "entrepreneurial identity" of startup founders and then study how a variation in identity salience influences their willingness to make certain choices in hypothetical scenarios.

Research in psychology posits that individuals have multiple identities centered around the different social roles they occupy, and that their behavior at a given time may depend on which identity is dominant (Akerlof and Kranton, 2000). Priming interventions can cause a particular identity to become more salient, altering an individual's values and desires and, thus, his or her economic decisions (Benjamin et al, 2010). This study examines how the profit-maximizing strategic decisions of startups are constrained by the personal motivations of their utility-maximizing founders. In a novel experimental approach that integrates psychology, economics, and strategy research, we apply priming techniques to study entrepreneurial decision-making. In two experiments, we prime entrepreneurs' "entrepreneurial identity" through a survey mechanism. Entrepreneurs are randomly distributed either the priming or the control version of the survey. The priming questionnaire asks four questions about their startup strategy (e.g., "What is your exit strategy?"), while the control questionnaire asks four questions about their work-life balance (e.g., "Whom do you typically spend leisure time with?").

Experiment 1 (Manipulation Check): The purpose of the first experiment is to verify that our priming intervention does increase "entrepreneurial identity." Our sample for the first experiment consists of 90 entrepreneurs recruited through Qualtrics Online Samples, and we screen out those who have companies older than 5 years. After answering the priming or control questions, both priming and control groups complete a word-choice test to measure the dominance of their entrepreneurial identities. Subjects are asked to choose the word that best describes them from a series of ten word pairs. In each pair, one word is entrepreneurial (i.e., "innovative") and one is not (i.e., "generous"). We expect that the priming group will have a higher average of entrepreneurial words selected. We also use this first experiment as an opportunity to test the hypothetical scenario questions described below, and we intend to use the experimental results from this study for our power calculations.

Experiment 2 (Main Experiment): Our main sample is drawn from a population of entrepreneurs who have registered for a free online class that will be taught by one of us. Entrepreneurs are asked to complete a 10-minute registration form with questions about their personal and startup backgrounds. We screen our registrants to select growth-driven startups that are not more than 5 years old. Several weeks after registering for the class, subjects are requested to complete a pre-class survey. The pre-class survey is again either the priming or control condition, consisting of the same priming or control questions, followed by questions about how the subject would behave in the following hypothetical scenarios. We designed these questions to specify a trade-off between startup growth and personal utility:

A. A major Silicon Valley venture capital firm has contacted you to express interest in investing in your startup. The firm has a history of partnerships with numerous highly-successful companies, and Series A investments in its partners are typically around $5 million. However, the firm only invests in startups that are located in Silicon Valley. How likely would you be to decide to move to Silicon Valley?

B. For the last month, you have been employing a close relative to do part-time work for your startup. However, the quality of their work is below expectations, often requiring you to spend extra time correcting their errors. You have spoken to the relative regarding your concerns, but the errors still continue. How likely would you be to fire your relative?

C. You have planned a long vacation to spend some quality time with your family and/or your closest friends, but you have just been invited to a special event where you will have the opportunity to network with numerous potential investors. This event is going to be held during the time you had planned to be on vacation. How likely would you be to cancel your vacation?

D. Your startup has the opportunity to make an investment that may greatly increase growth in the future. In order to finance the investment, you would have to nearly drain your own retirement savings. How likely would you be to make the investment?

We examine the discrepancy between the priming and control groups to elucidate how personal costs constrain strategic decision-making.

Prior to this trial registration, we conducted a pilot on a sample of 12 entrepreneurs recruited through Qualtrics Online Samples (a different sample than the one that will be used in the manipulation check described above). The data and R scripts used are attached to this trial registration.

Study 1: 45 primed and 45 control. Random assignment through Qualtrics in their outreach approach.
Study 2: 250 primed and 250 control. Block randomization, the values of which will be chosen based on the characteristics provided by the (class) pre-registration of the subjects. Potential candidates in this randomization are gender, marital status, and age, but we would like to see the distribution of this variables in the data first before randomizing.

We will amend our pre-registration when we have the class subjects identified to we can better state our randomization approach before study 2 has taken place.

We will amend our pre-registration when we have the class subjects identified to we can better state our randomization approach before study 2 has taken place.

No

We will amend our pre-registration when we have the class subjects identified to we can better state our randomization approach before study 2 has taken place.

Study 1: We recruit 90 entrepreneurs registered with Qualtrics Panels. Study 2: We hope to register 1000 individuals in our class, but after screening and attrition our target is to have about 500 subjects for analysis.

Study 1: 45 primed and 45 control.
Study 2: 250 primed and 250 control.

We do not have good priors on the amount of power necessary to identify our effects, as there is no established value in the literature that can help guide our analysis. We believe that doing any power calculations at this stage would simply not be useful. We do note that we can take advantage of the fact that we have two different studies to assess the validity and necessary power from one to the other, and hope to do so accordingly. We also intend in updating our pre-registration by the end of study 1, with our measure of power for Study 2.